Results 81 to 90 of about 2,204,167 (303)

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

Network Representation Learning

大数据, 2015
Along with the constant growth of massive online social networks such as Facebook,Twitter,Weixin and Weibo,a tremendous amount of network data sets are generated.How to represent the data is an important aspect when we apply machine learning techniques ...
Weizheng Chen, Yan Zhang, Xiaoming Li
doaj  

Representation Learning for cold-start recommendation

, 2014
A standard approach to Collaborative Filtering (CF), i.e. prediction of user ratings on items, relies on Matrix Factorization techniques. Representations for both users and items are computed from the observed ratings and used for prediction ...
Artieres, Thierry, Contardo, Gabriella, Denoyer, Ludovic   +2 more
core   +1 more source

Relation-First Modeling Paradigm for Causal Representation Learning toward the Development of AGI [PDF]

, 2023
Jia Li, Xiang Li
openalex   +1 more source

Continual Unsupervised Representation Learning

, 2019
NeurIPS ...
Rao, D, Visin, F, Rusu, AA, Teh, YW, Pascanu, R, Hadsell, R   +5 more
openaire   +3 more sources

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

ViewMix: Augmentation for Robust Representation in Self-Supervised Learning [PDF]

, 2023
Arjon Das, Xin Zhong
openalex   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Understanding Dynamics of Nonlinear Representation Learning and Its Application [PDF]

, 2022
Kenji Kawaguchi, Linjun Zhang, Zhun Deng
openalex   +1 more source

Towards Learning Word Representation

Schedae Informaticae, 2017
Continuous vector representations, as a distributed representations for words have gained a lot of attention in Natural Language Processing (NLP) field. Although they are considered as valuable methods to model both semantic and syntactic features, they still may be improved.
openaire   +3 more sources